In general, a time series algorithm attempts to predict a future result based on past data. Microsoft Corporation provided a time series algorithm in SQL Server based on an algorithm referred to as ARTXP (Auto regressive tree with cross prediction) for forecasting.
The ARTXP algorithm is highly optimized for near term predictions, and thus very good at forecasting them. However the algorithm's accuracy degraded for long term predictions. It was occasionally unstable for long term predictions which made it sometimes unusable beyond the first few time stamps for which a forecast was requested.
In a later version, namely SQL Server 2008, forecasting was implemented via the well-known ARIMA (Auto regressive integrated moving average) algorithm for time series forecasting. ARIMA is known to have stable long term forecasting characteristics.